Sensor-based Waste Handling System
Vishnu Chithan.S1, Rajagopal.S2, P.Shanmugapriya3
1Vishnu Chithan.S, Department of Computer Science and Engineering SCSVMV University, Kanchipuram.
2Rajagopal. S, Department of Computer Science and Engineering SCSVMV University, Kanchipuram.
3Dr.P.Shanmugapriya, Department of Computer Science and Engineering SCSVMV University, Kanchipuram.
Manuscript received on April 20, 2020. | Revised Manuscript received on April 30, 2020. | Manuscript published on May 10, 2020. | PP: 536-540 | Volume-9 Issue-7, May 2020. | Retrieval Number: G5120059720/2020©BEIESP | DOI: 10.35940/ijitee.G5120.059720
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Earlier, separation of waste objects was a tedious process for humans since it requires thorough identification of each object’s nature. The identification and segregation of waste products are indispensable processes. The project consists of an Image Classification section where the waste is captured with the help of Raspberry pi camera and processed in the appropriate environment to classify if the waste is biodegradable or non biodegradable. The classified image is set with a key and delivered to the breadboard which is connected with Raspberry pi to illuminate the LED accordingly. The untrained or unidentified object is marked with a different LED and can be left for a new training process so that the system collects the features of the particular object and be ready with a model. Following is the Waste Management System. An Ultrasonic sensor is placed at the corner to dump the waste in the corresponding bin with the help of servo motor, which contributes to swap the bins by rotating itself in 180 degrees when non-biodegradable waste is identified. The classified object is disposed in its bin which concludes both the classification and segregation processes. Manual labour is minimized through this automatic waste identification and disposal.
Keywords: Raspberry pi camera, Ultrasonic sensor, untrained object, Image Classification, Waste management system
Scope of the Article: Classification